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    <title>cdff</title>
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    <center>Scilab Function</center>
    <div align="right">Last update : Dec 1997</div>
    <p>
      <b>cdff</b> -  cumulative distribution function F distribution</p>
    <h3>
      <font color="blue">Calling Sequence</font>
    </h3>
    <dl>
      <dd>
        <tt>[P,Q]=cdff("PQ",F,Dfn,Dfd)  </tt>
      </dd>
      <dd>
        <tt>[F]=cdff("F",Dfn,Dfd,P,Q);  </tt>
      </dd>
      <dd>
        <tt>[Dfn]=cdff("Dfn",Dfd,P,Q,F);  </tt>
      </dd>
      <dd>
        <tt>[Dfd]=cdff("Dfd",P,Q,F,Dfn)  </tt>
      </dd>
    </dl>
    <h3>
      <font color="blue">Parameters</font>
    </h3>
    <ul>
      <li>
        <tt>
          <b>P,Q,F,Dfn,Dfd</b>
        </tt>: five real vectors of the same size.</li>
      <li>
        <tt>
          <b>P,Q (Q=1-P)  </b>
        </tt>:  The integral from 0 to F of the f-density. Input range: [0,1].</li>
      <li>
        <tt>
          <b>F</b>
        </tt>: Upper limit of integration of the f-density. Input range: [0, +infinity). Search range: [0,1E300]</li>
      <li>
        <tt>
          <b>Dfn</b>
        </tt>: Degrees of freedom of the numerator sum of squares. Input range: (0, +infinity). Search range: [ 1E-300, 1E300]</li>
      <li>
        <tt>
          <b>Dfd</b>
        </tt>: Degrees of freedom of the denominator sum of squares. Input range: (0, +infinity). Search range: [ 1E-300, 1E300]</li>
    </ul>
    <h3>
      <font color="blue">Description</font>
    </h3>
    <p>
    Calculates any one parameter of the F distribution
    given values for the others.</p>
    <p>
    Formula   26.6.2   of   Abramowitz   and   Stegun,  Handbook  of
    Mathematical  Functions (1966) is used to reduce the computation
    of the  cumulative  distribution function for the  F  variate to
    that of an incomplete beta.</p>
    <p>
    Computation of other parameters involve a seach for a value that
    produces  the desired  value  of P.   The search relies  on  the
    monotinicity of P with the other parameter.</p>
    <p>
    The value of the  cumulative  F distribution is  not necessarily
    monotone in  either degrees of freedom.  There  thus may  be two
    values  that  provide a given CDF  value.   This routine assumes
    monotonicity and will find an arbitrary one of the two values.</p>
    <p>
    From DCDFLIB: Library of Fortran Routines for Cumulative Distribution
    Functions, Inverses, and Other Parameters (February, 1994)
    Barry W. Brown, James Lovato and Kathy Russell. The University of
    Texas.</p>
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